Real-time Event Detection in Twitter: A Case Study

Abstract

In this paper we present the study which uses hashing as a vectorizer and locality sensitive hashing to approximately find similar items, combined with incremental clustering to implement a practical real-time event detection algorithm. By gathering a substantial amount of Persian tweets, the proposed algorithm is evaluated. It is shown that the presented pipeline and methods are capable of detecting the events related to 7 out of 10 football matches during the days in which the Iranian national football team took part in the 2018 FIFA World Cup. A total of 102 events were detected with a precision of 87.25%.